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Suppress scikit-learn DeprecationWarning in hyperopt

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hroff-1902 2019-05-15 13:35:09 +03:00
parent 6d17cd50fe
commit 64becdf895
3 changed files with 33 additions and 4 deletions
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4
freqtrade/optimize/default_hyperopt.py
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@ -5,10 +5,10 @@ from pandas import DataFrame
from typing import Dict, Any, Callable, List
from functools import reduce
from skopt.space import Categorical, Dimension, Integer, Real
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_interface import Categorical, Dimension, Integer, Real
class_name = 'DefaultHyperOpts'

30
freqtrade/optimize/hyperopt_interface.py
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@ -7,7 +7,35 @@ from abc import ABC, abstractmethod
from typing import Dict, Any, Callable, List
from pandas import DataFrame
from skopt.space import Dimension
#
# Filter warnings from importing scikit-learn via skopt.
# scikit-learn specifically forces warnings to be displayed, which we don't like.
#
# See:
# https://github.com/scikit-learn/scikit-learn/issues/2531
# https://github.com/ims-tcl/DeRE/commit/cb865fedddf6977cb7536b8c4334dc2325d09e53
# https://stackoverflow.com/questions/32612180/eliminating-warnings-from-scikit-learn
# for more details.
#
# Use
# from freqtrade.optimize.hyperopt_interface import Categorical, Dimension, Integer, Real
# instead of
# from skopt.space import Categorical, Dimension, Integer, Real
# in the custom HyperOpts to get rid of this deprecation warning
# (refer to default_hyperopt.py for example) without implementing this ugly
# workaround in every custom HyperOpts.
#
# Let's wait till scikit-learn v0.23 and skopt using it
# where it will probably be eliminated...
#
import warnings
def warn(*args, **kwargs):
pass
old_warn = warnings.showwarning
warnings.showwarning = warn
from skopt.space import Categorical, Dimension, Integer, Real
warnings.showwarning = old_warn
class IHyperOpt(ABC):

3
user_data/hyperopts/sample_hyperopt.py
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@ -6,10 +6,11 @@ from typing import Dict, Any, Callable, List
from functools import reduce
import numpy
from skopt.space import Categorical, Dimension, Integer, Real
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_interface import Categorical, Dimension, Integer, Real
class_name = 'SampleHyperOpts'